Data‐Driven Design of NiHCF‐Based Mixed‐Matrix Membranes for CO ₂ Capture: Linking Material Screening, Process Simulation, and Life Cycle Assessment

The development of sustainable carbon capture technologies requires integrating advanced materials and conducting system‐level evaluation. Here, we present a data‐driven framework for designing mixed‐matrix membranes incorporating Nickel Hexacyanoferrate (NiHCF), a Prussian blue analogue, for CO 2 separation. A CO 2 ‐responsive solution‐acidification screening method was developed to rapidly assess the CO2 interaction behavior of NiHCF particles synthesized under different conditions. Machine learning was then used to identify key synthesis parameters and guide material optimization. The optimized NiHCF exhibited enhanced CO 2 interaction, leading to improved membrane performance. Notably, a strong correlation between the screening response and CO 2 /N 2 selectivity was observed (R 2 = 0.95), indicating that the proposed screening strategy can serve as a predictive indicator of membrane performance before fabrication. Molecular dynamics simulations further revealed that NiHCF incorporation enhances CO 2 capture behavior by improving thermodynamic stability, CO 2 diffusion, intermolecular equilibration, and adsorption interactions. Life‐cycle assessment showed that the optimized membrane system can reduce the operational carbon footprint compared with the pristine membrane, despite a higher footprint during fabrication. Finally, process simulation was conducted to evaluate practical separation performance and CO 2 capture feasibility under defined assumptions. This study links data‐driven material design with molecular insight, environmental sustainability assessment, and process‐level evaluation.